使用beautifulsoup的解决方案：

from bs4 import BeautifulSoup

with open("your_file.xml", "r") as f_in:
    soup = BeautifulSoup(f_in.read(), "xml")

def parse_columns(t):
    out = {}
    for c in t.find_all("column", recursive=False):
        if c.find("column"):
            out[c["name"]] = parse_columns(c)
        else:
            out[c["name"]] = c["type"]
    return out

def parse_schema(sch):
    out = {}
    for t in sch.select("table"):
        out[t["name"]] = parse_columns(t)
    return out

out = {}
for sch in soup.select("schema"):
    out[sch["name"]] = parse_schema(sch)

print(out)

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印刷品：

{
    "database1": {
        "table1": {
            "foo": "int",
            "bar": "string",
            "details_resolution": {
                "timestamp": "timestamp",
                "user_id": "string",
                "user_name": "string",
            },
            "details_closure": {"timestamp": "timestamp", "auto_closure": "bool"},
        }
    },
    "database2": {
        "table1": {
            "foo": "int",
            "bar": "string",
            "details": {"timestamp": "timestamp", "value": "float"},
        }
    },
}

型

可以使用xml.etree.ElementTree

import xml.etree.ElementTree as ET

def parse_column(column_elem):
    column_data = {}
    column_data['name'] = column_elem.get('name')
    column_data['type'] = column_elem.get('type')
    return column_data

def parse_table(table_elem):
    table_data = {}
    table_name = table_elem.get('name')
    for column_elem in table_elem.findall('column'):
        column_data = parse_column(column_elem)
        table_data[column_data['name']] = column_data['type']
    return {table_name: table_data}

def parse_schema(schema_elem):
    schema_data = {}
    schema_name = schema_elem.get('name')
    for table_elem in schema_elem.findall('table'):
        table_data = parse_table(table_elem)
        schema_data.update(table_data)
    return {schema_name: schema_data}

def parse_xml(xml_content):
    root = ET.fromstring(xml_content)
    project_data = {}
    for schema_elem in root.findall('schema'):
        schema_data = parse_schema(schema_elem)
        project_data.update(schema_data)
    return project_data

# Read XML file
with open('file.xml', 'r') as f:
    xml_content = f.read()

# Parse XML and generate nested dictionary
nested_dict = parse_xml(xml_content)
print(nested_dict)

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在XSLT 3.0中：

<xsl:output method="json" indent="yes" />
  
  <xsl:template match="/">
    <xsl:map>
      <xsl:apply-templates select="*/schema"/>
    </xsl:map>
  </xsl:template>

  <xsl:template match="*[*]">
     <xsl:map-entry key="string(@name)">
        <xsl:map>
          <xsl:apply-templates select="*"/>
        </xsl:map>
     </xsl:map-entry>
  </xsl:template>
  
  <xsl:template match="*">
    <xsl:map-entry key="string(@name)" select="string(@type)"/>
  </xsl:template>

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请参阅https://xsltfiddle.liberty-development.net/bdvWh3以获取完整的样式表，包括样板文件。
说明：

• 第一个模板规则匹配文档，创建最外层的Map，并处理schema元素，跳过project级别。
• 第二模板规则匹配具有一个或多个子级的元素;它以@name属性作为键为容器元素创建Map条目，并通过将模板规则递归地应用于子元素来生成另一Map作为内容。
• 第三个模板规则匹配没有子元素的元素;它为容器元素创建一个Map条目，其中@name作为键，@type作为相应的值。